Norah Saleh Alghamdi¹, Sami Bourouis^2,*, Nizar Bouguila³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1139-1156, 2022, DOI:10.32604/cmc.2022.022959 - 24 February 2022

Abstract Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security applications. In particular, recognizing human activities with accurate results have become a topic of high interest. Although the current tools have reached remarkable successes, it is still a challenging problem due to various uncontrolled environments and conditions. In this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some real-world applications. In particular, two nonparametric hierarchical Bayesian models based on Dirichlet process… More >

Faheem Khan¹, Muhammad Zahid², Hüseyin Gürüler³, Ilhan Tarimer³, Taegkeun Whangbo^1,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 663-678, 2022, DOI:10.32604/cmc.2022.022934 - 24 February 2022

Abstract The Internet of thing (IoT) is a growing concept for smart cities, and it is compulsory to communicate data between different networks and devices. In the IoT, communication should be rapid with less delay and overhead. For this purpose, flooding is used for reliable data communication in a smart cities concept but at the cost of higher overhead, energy consumption and packet drop etc. This paper aims to increase the efficiency in term of overhead and reliability in term of delay by using multicasting and unicasting instead of flooding during packet forwarding in a smart… More >

Rohit Raja¹, Chetan Swarup², Abhishek Kumar^3,*, Kamred Udham Singh⁴, Teekam Singh⁵, Dinesh Gupta⁶, Neeraj Varshney⁷, Swati Jain⁸

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2015-2031, 2022, DOI:10.32604/cmc.2022.022904 - 24 February 2022

Abstract As far as the present state is concerned in detecting the behavioral pattern of humans (subject) using morphological image processing, a considerable portion of the study has been conducted utilizing frontal vision data of human faces. The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach. In this example, hybridization includes an artificial neural network (ANN) with a genetic algorithm (GA). We researched the geometrical properties extracted from side-vision human-face data. An additional study was conducted to determine the ideal number of… More >

Daniyal M. Alghazzawi¹, Osama Bassam J. Rabie¹, Surbhi Bhatia², Syed Hamid Hasan^1,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1173-1193, 2022, DOI:10.32604/cmc.2022.022748 - 24 February 2022

Abstract The Deep Neural Networks (DNN) training process is widely affected by backdoor attacks. The backdoor attack is excellent at concealing its identity in the DNN by performing well on regular samples and displaying malicious behavior with data poisoning triggers. The state-of-art backdoor attacks mainly follow a certain assumption that the trigger is sample-agnostic and different poisoned samples use the same trigger. To overcome this problem, in this work we are creating a backdoor attack to check their strength to withstand complex defense strategies, and in order to achieve this objective, we are developing an improved… More >

Hameed AlQaheri^1,*, Manash Sarkar², Saptarshi Gupta³, Bhavya Gaur⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 497-517, 2022, DOI:10.32604/cmc.2022.022735 - 24 February 2022

Abstract The most common alarming and dangerous disease in the world today is the coronavirus disease 2019 (COVID-19). The coronavirus is perceived as a group of coronaviruses which causes mild to severe respiratory diseases among human beings. The infection is spread by aerosols emitted from infected individuals during talking, sneezing, and coughing. Furthermore, infection can occur by touching a contaminated surface followed by transfer of the viral load to the face. Transmission may occur through aerosols that stay suspended in the air for extended periods of time in enclosed spaces. To stop the spread of the… More >

Khalil Ibrahim Mohammad Abuzanouneh¹, Fahd N. Al-Wesabi², Amani Abdulrahman Albraikan³, Mesfer Al Duhayyim⁴, M. Al-Shabi⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza^6,*, Abu Sarwar Zamani⁶, K. Muthulakshmi⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.022648 - 24 February 2022

Abstract Agriculture 4.0, as the future of farming technology, comprises numerous key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. To achieve effective water resource usage and automated irrigation in precision agriculture, recent technologies like machine learning (ML) can be employed. With this motivation, this paper design an IoT and ML enabled smart irrigation system (IoTML-SIS) for precision agriculture. The proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for… More >

Saima Kauser¹, Tauqeer Safdar Malik^1,*, Mohd Hilmi Hasan², Emelia Akashah P. Akhir², Syed Muhammad Husnain Kazmi³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1251-1273, 2022, DOI:10.32604/cmc.2022.022475 - 24 February 2022

Abstract A web browser is the most basic tool for accessing the internet from any of the machines/equipment. Recently, data breaches have been reported frequently from users who are concerned about their personal information, as well as threats from criminal actors. Giving loss of data and information to an innocent user comes under the jurisdiction of cyber-attack. These kinds of cyber-attacks are far more dangerous when it comes to the many types of devices employed in an internet of things (IoT) environment. Continuous surveillance of IoT devices and forensic tools are required to overcome the issues… More >

Khalid A. AlAfandy¹, Hicham Omara², Hala S. El-Sayed³, Mohammed Baz^4,*, Mohamed Lazaar⁵, Osama S. Faragallah⁶, Mohammed Al Achhab¹

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 739-753, 2022, DOI:10.32604/cmc.2022.022457 - 24 February 2022

Abstract Remote sensing image processing engaged researchers’ attentiveness in recent years, especially classification. The main problem in classification is the ratio of the correct predictions after training. Feature extraction is the foremost important step to build high-performance image classifiers. The convolution neural networks can extract images’ features that significantly improve the image classifiers’ accuracy. This paper proposes two efficient approaches for remote sensing images classification that utilizes the concatenation of two convolution channels’ outputs as a features extraction using two classic convolution models; these convolution models are the ResNet 50 and the DenseNet 169. These elicited… More >

Yuan Chen¹, Yulu Tian¹, Dingfan Zhang², Longting Huang^3,*, Jingxin Xu⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1671-1684, 2022, DOI:10.32604/cmc.2022.022371 - 24 February 2022

Abstract In many applications such as multiuser radar communications and astrophysical imaging processing, the encountered noise is usually described by the finite sum of -stable variables. In this paper, a new parameter estimator is developed, in the presence of this new heavy-tailed noise. Since the closed-form PDF of the -stable variable does not exist except and , we take the sum of the Cauchy () and Gaussian () noise as an example, namely, additive Cauchy-Gaussian (ACG) noise. The probability density function (PDF) of the mixed random variable, can be calculated by the convolution of the Cauchy's… More >

Ibrahim M. Mehedi^1,2,*, Maher H. AL-Sereihy², Asmaa Ubaid Al-Saggaf², Ubaid M. Al-Saggaf^1,2

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 651-662, 2022, DOI:10.32604/cmc.2022.022013 - 24 February 2022

Abstract Tracking load changes in a pressurized water reactor (PWR) with the help of an efficient core power control scheme in a nuclear power station is very important. The reason is that it is challenging to maintain a stable core power according to the reference value within an acceptable tolerance for the safety of PWR. To overcome the uncertainties, a non-integer-based fractional order control method is demonstrated to control the core power of PWR. The available dynamic model of the reactor core is used in this analysis. Core power is controlled using a modified state feedback More >